Google Cloud foundations, projects, networking, Cloud Run, GKE, data, AI, security, delivery, migration, and managed operation

Google Cloud engineering services

Rokad designs, builds, migrates, secures, and operates Google Cloud environments across resource hierarchy, networking, applications, containers, data, AI, and reliability.

Cloud platform engineering Discuss this platform project

Platform fit / 01

Designed for teams with a specific platform requirement.

Google Cloud combines strong container, serverless, data, analytics, and AI capabilities with a project-oriented resource model. Rokad designs organisations, folders, projects, identity, networks, policies, application services, data platforms, observability, recovery, cost, and delivery around workload and ownership boundaries.

Product and data teams building on Google Cloud

Create governed foundations for Cloud Run, GKE, APIs, event systems, databases, BigQuery, analytics, and AI workloads.

Organisations migrating applications or analytical estates

Move services and data with project, network, identity, cutover, validation, recovery, and operational transition controls.

Companies rationalising project and billing sprawl

Standardise folders, projects, IAM, networks, service accounts, logging, security, budgets, labels, and support ownership.

Implementation risks / 02

The platform problems Rokad is prepared to solve.

Projects were created without a durable organisation model

Environments, business domains, data, networks, billing, policies, logs, and ownership do not align.

Service accounts and keys create hidden trust paths

Broad roles, long-lived keys, cross-project access, unmanaged secrets, and weak workload identity increase exposure.

Data and application platforms are operated separately

Cloud Run, GKE, BigQuery, storage, messaging, AI, monitoring, and networking lack a coordinated reliability and cost model.

Platform capabilities / 03

What Rokad can implement and operate.

Google Cloud organisation, folders, projects, billing, policies, labels, shared VPC, and landing-zone architecture

Cloud Identity, IAM, service accounts, Workload Identity Federation, Secret Manager, KMS, audit logs, and policy

VPC, Shared VPC, private service access, Cloud DNS, load balancing, Cloud CDN, Interconnect, and hybrid connectivity

Cloud Run, GKE, Compute Engine, Functions, API Gateway, Apigee, Pub/Sub, and event-driven architecture

Cloud Storage, Cloud SQL, AlloyDB, Spanner, Firestore, BigQuery, data movement, backup, and recovery

Terraform, Cloud Build, GitHub Actions, artefacts, environments, progressive delivery, observability, and automation

Cloud Operations, Security Command Center, vulnerability, incident, capacity, performance, cost, and managed operation

Implementation system / 04

The architecture behind a dependable platform delivery.

Google Cloud foundation

Organisation, folders, projects, identity, billing, networks, policy, logging, security, budgets, and shared services.

Application and data platform

Cloud Run, GKE, compute, APIs, events, storage, databases, BigQuery, AI, scaling, and failure domains.

Delivery and policy plane

Terraform, pipelines, artefacts, service identities, environments, approvals, policy, deployment, validation, and rollback.

Google Cloud operations

Metrics, logs, traces, objectives, incidents, backup, recovery, security findings, quotas, capacity, cost, and support.

Use cases / 05

Where this platform creates practical leverage.

Google Cloud landing zone

Create organisation, folder, project, network, identity, logging, policy, security, billing, and account-provisioning foundations.

Cloud Run and GKE application platform

Build scalable container and API workloads with managed identity, delivery, events, data, telemetry, and reliability controls.

Data and analytics foundation

Integrate storage, BigQuery, streaming, transformation, governance, BI, AI, and workload cost under one cloud architecture.

Google Cloud migration and modernisation

Move applications and data while improving service boundaries, networking, deployment, observability, recovery, and operating ownership.

Architecture / 06

Platform-specific engineering decisions and boundaries.

Project boundaries follow workload and policy ownership

Separate environments, domains, data, shared services, security, and billing where isolation, delegation, or lifecycle differ.

Workload Identity Federation reduces key distribution

Use short-lived identity for CI/CD, applications, and external systems instead of unmanaged service-account keys where supported.

Serverless and Kubernetes are selected by workload shape

Choose Cloud Run, GKE, functions, or virtual machines from traffic, runtime, networking, state, portability, and operational requirements.

Quality and governance / 07

Production controls are part of the implementation.

Secure cloud boundaries

Accounts, subscriptions, projects, identity, networks, secrets, encryption, policy, logs, and production access are designed as explicit trust boundaries.

Reproducible infrastructure

Infrastructure, configuration, policy, deployment, monitoring, backup, and recovery controls are versioned and delivered through reviewable automation.

Operated reliability and cost

Service objectives, telemetry, incidents, capacity, recovery, usage, commitments, budgets, and ownership are measured together.

Delivery / 08

A controlled path from assessment to operation.

Assess

Clarify the business outcome, current systems, platform constraints, data, integrations, risks, ownership, and measurable acceptance criteria.

Design

Define the platform architecture, workflow or storefront model, extensions, integrations, security, environments, and migration sequence.

Implement and validate

Build in controlled increments with testing, stakeholder review, observability, documentation, and platform-specific quality controls.

Launch and operate

Deploy safely, transfer ownership, monitor production behaviour, support users, and improve the implementation using operational evidence.

Typical platform deliverables

Google Cloud organisation, project, workload, network, identity, data, cost, and migration assessment

Landing-zone, application, data, integration, reliability, and governance architecture

Terraform repositories, resource hierarchy, shared networking, policy, and platform foundations

Cloud Run, GKE, compute, API, event, storage, database, and analytical implementation

CI/CD, Cloud Operations, security, backup, recovery, cost, and incident controls

Architecture decisions, runbooks, ownership, support, and handover documentation

Engagement models / 09

Use the delivery structure that matches the platform work.

Assessment and roadmap

A bounded review of the current platform, requirements, gaps, risks, architecture, and an executable next-stage plan.

Fixed-scope implementation

A defined integration, migration, storefront, application, workflow, or platform outcome with explicit acceptance criteria.

Embedded platform specialists

Specialists working alongside internal product, engineering, operations, marketing, data, or enterprise teams.

Managed platform evolution

Ongoing maintenance, releases, integrations, support, optimisation, governance, and roadmap execution after launch.

Related platforms and services / 10

Compare adjacent platforms or continue into the wider system.

Amazon Web Services

AWS account, application, container, data, security, migration, and operating platform engineering.

Microsoft Azure

Azure landing zones, Entra identity, applications, data, AKS, security, and operations.

Cloudflare

Edge compute, delivery, storage, networking, security, and Zero Trust platform engineering.

Software development

Custom applications, backends, integrations, APIs, marketplaces, and enterprise systems.

Data engineering

Pipelines, platforms, warehouses, analytics engineering, BI, and governed data operations.

AI development

AI applications, agents, retrieval, evaluation, model integration, and intelligent workflows.

FAQ

Google Cloud engineering services

Platform scope, ownership, licences, data, integrations, security, migration, and long-term operation are clarified before delivery.

Can Rokad design a Google Cloud organisation and project structure?

Yes. We map teams, environments, workloads, data, policies, networks, billing, and support into a resource hierarchy with controlled delegation.

Should our application use Cloud Run or GKE?

The choice depends on runtime control, traffic, networking, state, sidecars, portability, scaling, team capability, and total operating effort. We evaluate the workload before selecting the platform.

Can Rokad integrate BigQuery and AI services with applications?

Yes. We design identity, data, APIs, events, pipelines, governance, cost, latency, and operational boundaries across application, analytics, and AI workloads.

Can Rokad operate Google Cloud after launch?

Yes. Managed services can include releases, monitoring, incidents, security, backups, recovery, upgrades, quotas, capacity, cost, and platform evolution.

Google Cloud · Cloud platform engineering

Build Google Cloud around application, data, and operating boundaries that remain clear at scale.

Rokad can establish the foundation, implement Cloud Run, GKE, data and AI workloads, migrate systems, and operate the platform.

Discuss Google Cloud

Contact / 05

Bring us the difficult technology problem.

Tell us what you need to build, improve, procure, deploy, or operate. We will respond with a practical next step.

Direct email

sales@rokad.co

Response

Within one business day

Delivery

India and global